{"title":"利用高效的预测算法降低H.264视频编码中离散余弦变换/量化/反量化/反离散余弦变换的计算复杂度","authors":"Chih-Ling Hsu, Chang-Hsin Cheng","doi":"10.1049/IET-IPR.2008.0213","DOIUrl":null,"url":null,"abstract":"This study develops a novel prediction algorithm to effectively save the computational complexity of discrete cosine transform (DCT), quantisation (Q), inverse Q (IQ), and inverse DCT (IDCT) in video encoding for H.264 applications. Based on the DC value of the DCT coefficients that is equal to the sum of residual data in the 4×4 sub-macroblock (sub-MB), a mathematical model is built to develop a prediction algorithm for reducing the computations in the DCT/Q/IQ/IDCT process. Experimental results and comparisons demonstrate that the proposed prediction algorithm significantly reduces the encoding time while incurring little additional overhead, and lowers the bit rate with little peak signal-to-noise ratio degradation.","PeriodicalId":13486,"journal":{"name":"IET Image Process.","volume":"128 1","pages":"177-187"},"PeriodicalIF":0.0000,"publicationDate":"2009-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Reduction of discrete cosine transform/quantisation/inverse quantisation/inverse discrete cosine transform computational complexity in H.264 video encoding by using an efficient prediction algorithm\",\"authors\":\"Chih-Ling Hsu, Chang-Hsin Cheng\",\"doi\":\"10.1049/IET-IPR.2008.0213\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study develops a novel prediction algorithm to effectively save the computational complexity of discrete cosine transform (DCT), quantisation (Q), inverse Q (IQ), and inverse DCT (IDCT) in video encoding for H.264 applications. Based on the DC value of the DCT coefficients that is equal to the sum of residual data in the 4×4 sub-macroblock (sub-MB), a mathematical model is built to develop a prediction algorithm for reducing the computations in the DCT/Q/IQ/IDCT process. Experimental results and comparisons demonstrate that the proposed prediction algorithm significantly reduces the encoding time while incurring little additional overhead, and lowers the bit rate with little peak signal-to-noise ratio degradation.\",\"PeriodicalId\":13486,\"journal\":{\"name\":\"IET Image Process.\",\"volume\":\"128 1\",\"pages\":\"177-187\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-09-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IET Image Process.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1049/IET-IPR.2008.0213\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IET Image Process.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1049/IET-IPR.2008.0213","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Reduction of discrete cosine transform/quantisation/inverse quantisation/inverse discrete cosine transform computational complexity in H.264 video encoding by using an efficient prediction algorithm
This study develops a novel prediction algorithm to effectively save the computational complexity of discrete cosine transform (DCT), quantisation (Q), inverse Q (IQ), and inverse DCT (IDCT) in video encoding for H.264 applications. Based on the DC value of the DCT coefficients that is equal to the sum of residual data in the 4×4 sub-macroblock (sub-MB), a mathematical model is built to develop a prediction algorithm for reducing the computations in the DCT/Q/IQ/IDCT process. Experimental results and comparisons demonstrate that the proposed prediction algorithm significantly reduces the encoding time while incurring little additional overhead, and lowers the bit rate with little peak signal-to-noise ratio degradation.